DLP: Duplex Link Prediction Via Subspace Segmentation for Predicting drug-MiRNA Associations.

The arduous and costly journey of drug discovery is increasingly intersecting with computational approaches, which promise to accelerate the analysis of bioassays and biomedical literature. The critical role of microRNAs (miRNAs) in disease progression has been underscored in recent studies, elevating them as potential therapeutic targets. This emphasizes the need for the development of sophisticated computational models that can effectively identify promising drug targets, such as miRNAs. Herein, we present a novel method, termed Duplex Link Prediction (DLP), rooted in subspace segmentation, to pinpoint potential miRNA targets. Our approach initiates with the application of the Network Enhancement (NE) algorithm to refine the similarity metric between miRNAs. Thereafter, we construct two matrices by pre-loading the association matrix from both the drug and miRNA perspectives, employing the K Nearest Neighbors (KNN) technique. The DLSR algorithm is then applied to predict potential associations. The final predicted association scores are ascertained through the weighted mean of the two matrices. Our empirical findings suggest that the DLP algorithm outperforms current methodologies in the realm of identifying potential miRNA drug targets. Case study validations further reinforce the real-world applicability and effectiveness of our proposed method. The code of DLP is freely available at https://github.com/kaizheng-academic/DLP.

GSScore: a novel Graphormer-based shell-like scoring method for protein-ligand docking.

Protein-ligand interactions (PLIs) are essential for cellular activities and drug discovery. But due to the complexity and high cost of experimental methods, there is a great demand for computational approaches to recognize PLI patterns, such as protein-ligand docking. In recent years, more and more models based on machine learning have been developed to directly predict the root mean square deviation (RMSD) of a ligand docking pose with reference to its native binding pose. However, new scoring methods are pressingly needed in methodology for more accurate RMSD prediction. We present a new deep learning-based scoring method for RMSD prediction of protein-ligand docking poses based on a Graphormer method and Shell-like graph architecture, named GSScore. To recognize near-native conformations from a set of poses, GSScore takes atoms as nodes and then establishes the docking interface of protein-ligand into multiple bipartite graphs within different shell ranges. Benefiting from the Graphormer and Shell-like graph architecture, GSScore can effectively capture the subtle differences between energetically favorable near-native conformations and unfavorable non-native poses without extra information. GSScore was extensively evaluated on diverse test sets including a subset of PDBBind version 2019, CASF2016 as well as DUD-E, and obtained significant improvements over existing methods in terms of RMSE, $R$ (Pearson correlation coefficient), Spearman correlation coefficient and Docking power.

[Fertility preservation through natural and artificial ovaries: a review].

Ovarian tissue cryopreservation (OTC) is currently the exclusive choice for preserving fertility in both young girls before reaching puberty and young women who require immediate chemotherapy. Ovarian tissue transplantation has proven to be effective in restoring hormonal cycles and fertility. However, in certain cancer cases, there is a potential risk of inadvertently reintroducing malignant cells when transplanting cryopreserved ovarian tissue. Therefore, the use of an artificial ovary as an innovative and complementary approach allows for the development of isolated follicles, facilitates oocyte maturation and ovulation, and can partially restore endocrine function. This paper presents a comprehensive overview of techniques used to preserve fertility in natural ovarian tissues, including slow freezing, vitrification and hydrogel encapsulation methods. Additionally, it reviews fertility preservation techniques for artificial ovarian tissues, such as strategies involving hydrogel-encapsulated follicle, scaffolding for constructing ovarian microtissues, and 3D printing engineering. Lastly, this article explores current challenges and difficulties encountered in preserving ovarian tissue fertility, while also anticipating future trends in development, making it a valuable reference for the implementation of ovarian tissue fertility preservation.

Preparing a Mice Model of Severe Acute Pancreatitis via a Combination of Caerulein and Lipopolysaccharide Intraperitoneal Injection.

The treatment of severe acute pancreatitis (SAP), with high mortality rates, poses a significant clinical challenge. Investigating the pathological changes associated with SAP using animal models can aid in identifying potential therapeutic targets and exploring novel treatment approaches. Previous studies primarily induced pancreatic injury through retrograde bile duct injection of sodium taviaurocholate, but the impact of surgical damage on the quality of the animal model remains unclear. In this study, we employed various frequencies of intraperitoneal Caerulein injections combined with different doses of LPS to induce pancreatic injury in C57BL/6J mice and compared the extent of injury across five intraperitoneal injection protocols. Regarding inducing acute pancreatitis in mice, an intraperitoneal injection protocol is proposed that results in a mortality rate as high as 80% within 5 days. Specifically, mice received ten daily intraperitoneal injections of Caerulein (50 µg/kg), followed by an injection of LPS (15 mg/kg) one hour after the last Caerulein administration. By adjusting the frequency and dosage of injected medications, one can manipulate the severity of pancreatic injury effectively. This model exhibits strong controllability and has a short replication cycle, making it feasible for completion by a single researcher without requiring expensive equipment. It conveniently and accurately simulates key disease characteristics observed in human SAP while demonstrating a high degree of reproducibility.

Translational PET Imaging of Nectin-4 Expression in Multiple Different Cancers with 68Ga-N188.

Nectin cell adhesion molecule 4 (nectin-4) is a transmembrane protein overexpressed on a variety of cancers and plays an important role in oncogenic and metastatic processes. The nectin-4-targeted antibody-drug conjugate enfortumab vedotin has been approved for treating locally advanced or metastatic urothelial cancer, but the efficacy in other types of cancer remains to be explored. The aim of this study was to evaluate the feasibility of nectin-4-targeted PET imaging with 68Ga-N188 as a noninvasive method to quantify membranous nectin-4 expression in multiple tumor types-an approach that may provide insight for patient stratification and treatment selection. Methods: Sixty-two patients with 16 types of cancer underwent head-to-head 68Ga-N188 and 18F-FDG PET/CT imaging for initial staging or detection of recurrence and metastases. Correlation between lesion SUVmax and nectin-4 expression determined by immunohistochemistry staining was analyzed in 36 of 62 patients. Results: The SUVmax of 68Ga-N188 had a positive correlation with membranous nectin-4 expression in the various tumor types tested (r = 0.458; P = 0.005), whereas no association was observed between the SUVmax and cytoplasmic nectin-4 expression. The detection rates for patient-based analysis of 68Ga-N188 and 18F-FDG PET/CT examinations were comparable (95.00% [57/60] vs. 93.33% [56/60]). In patients with pancreatic cancer, 68Ga-N188 exhibited a potential advantage for detecting residual or locally recurrent tumors; this advantage may assist in clinical decision-making. Conclusion: The correlation between nectin-4-targeted 68Ga-N188 PET imaging and membranous nectin-4 expression indicates the potential of 68Ga-N188 as an effective tool for selecting patients who may benefit from enfortumab vedotin treatment. The PET imaging results provided evidence to explore nectin-4-targeted therapy in a variety of tumors. 68Ga-N188 may improve the restaging of pancreatic cancer but requires further evaluation in a powered, prospective setting.

Calcitonin gene­related peptide alleviates hyperoxia­induced human alveolar cell injury via the CGRPR/TRPV1/Ca2+ axis.

Although exogenous calcitonin gene­related peptide (CGRP) protects against hyperoxia­induced lung injury (HILI), the underlying mechanisms remain unclear. The present study attempted to elucidate the molecular mechanism by which CGRP protects against hyperoxia­induced alveolar cell injury. Human alveolar A549 cells were treated with 95% hyperoxia to establish a hyperoxic cell injury model. ELISA was performed to detect the CGRP secretion. Immunofluorescence, quantitative (q)PCR, and western blotting were used to detect the expression and localization of CGRP receptor (CGRPR) and transient receptor potential vanilloid 1 (TRPV1). Cell counting kit­8 and flow cytometry were used to examine the proliferation and apoptosis of treated cells. Digital calcium imaging and patch clamp were used to analyze the changes in intracellular Ca2+ signaling and membrane currents induced by CGRP in A549 cells. The mRNA and protein expression levels of Cyclin D1, proliferating cell nuclear antigen (PCNA), Bcl­2 and Bax were detected by qPCR and western blotting. The expression levels of CGRPR and TRPV1 in A549 cells were significantly downregulated by hyperoxic treatment, but there was no significant difference in CGRP release between cells cultured under normal air and hyperoxic conditions. CGRP promoted cell proliferation and inhibited apoptosis in hyperoxia, but selective inhibitors of CGRPR and TRPV1 channels could effectively attenuate these effects; TRPV1 knockdown also attenuated this effect. CGRP induced Ca2+ entry via the TRPV1 channels and enhanced the membrane non­selective currents through TRPV1 channels. The CGRP­induced increase in intracellular Ca2+ was reduced by inhibiting the phospholipase C (PLC)/protein kinase C (PKC) pathway. Moreover, PLC and PKC inhibitors attenuated the effects of CGRP in promoting cell proliferation and inhibiting apoptosis. In conclusion, exogenous CGRP acted by inversely regulating the function of TRPV1 channels in alveolar cells. Importantly, CGRP protected alveolar cells from hyperoxia­induced injury via the CGRPR/TRPV1/Ca2+ axis, which may be a potential target for the prevention and treatment of the HILI.

Real-World Experience among Elderly Metastatic Breast Cancer Patients Treated with CDK4/6 Inhibitor-Based Therapy.

The largest portion of breast cancer patients diagnosed after 70 years of age present with hormone receptor-positive (HR+) breast cancer subtypes. Cyclin-dependent kinase (CDK) 4/6 inhibitor treatment, in conjunction with endocrine therapy, has become standard-of-care for metastatic HR+ breast cancer. In total, 320 patients with metastatic breast cancer receiving CDK4/6 inhibitor combined with fulvestrant or an aromatase inhibitor were enrolled in an ongoing observational study or were included in an IRB-approved retrospective study. All patients receiving CDK4/6 inhibitor-based therapy that were ≥70 years of age (n = 111) displayed prolonged progression-free survival (27.6 months) as compared to patients <70 years of age (n = 209, 21.1 months, HR = 1.38, p < 0.05). Specifically, patients receiving a CDK4/6 inhibitor with an aromatase inhibitor who were ≥70 years of age (n = 79) displayed exceptionally prolonged progression-free survival (46.0 months) as compared to patients receiving the same treatment who were <70 years of age (n = 161, 21.8 months, HR = 1.71, p < 0.01). However, patients ≥70 years of age also experienced more frequent adverse responses to CDK4/6 inhibitor-based treatment leading to dose reduction, hold, or discontinuation than the younger cohort (69% and 53%, respectively). Treatment strategies that may decrease toxicity without affecting efficacy (such as dose titration) are worth further exploration.

DTKGIN: Predicting drug-target interactions based on knowledge graph and intent graph.

Knowledge graph intent graph attention mechanism Predicting drug-target interactions (DTIs) plays a crucial role in drug discovery and drug development. Considering the high cost and risk of biological experiments, developing computational approaches to explore the interactions between drugs and targets can effectively reduce the time and cost of drug development. Recently, many methods have made significant progress in predicting DTIs. However, existing approaches still suffer from the high sparsity of DTI datasets and the cold start problem. In this paper, we develop a new model to predict drug-target interactions via a knowledge graph and intent graph named DTKGIN. Our method can effectively capture biological environment information for targets and drugs by mining their associated relations in the knowledge graph and considering drug-target interactions at a fine-grained level in the intent graph. DTKGIN learns the representation of drugs and targets from the knowledge graph and the intent graph. Then the probabilities of interactions between drugs and targets are obtained through the inner product of the representation of drugs and targets. Experimental results show that our proposed method outperforms other state-of-the-art methods in 10-fold cross-validation, especially in cold-start experimental settings. Furthermore, the case studies demonstrate the effectiveness of DTKGIN in predicting potential drug-target interactions. The code is available on GitHub: https://github.com/Royluoyi123/DTKGIN.

Impact of bioelectricity on DNRA process and microbial community composition within cathodic biofilms in dual-chambered bioelectrode microbial fuel cell (MFC).

The synchronous bioelectricity generation and dissimilatory nitrate reduction to ammonium (DNRA) pathway in Klebsiella variicola C1 was investigated. The presence of bioelectricity facilitated cell growth on the anodic biofilms, consequently enhancing the nitrate removal efficiency decreasing total nitrogen levels and causing a negligible accumulation of NO2- in the supernatant. Genomic analysis revealed that K. variicola C1 possessed a complete DNRA pathway and largely annotated electron shuttles. The up-regulated expression of genes narG and nirB, encoding nitrite oxidoreductase and nitrite reductase respectively, was closely associated with increased extracellular electron transfer (EET). High-throughput sequencing analysis was employed to investigate the impact of bioelectricity on microbial community composition within cathodic biofilms. Results indicated that Halomonas, Marinobacter and Prolixibacteraceae were enriched at the cathode electrodes. In conclusion, the integration of a DNRA strain with MFC facilitated the efficient removal of wastewater containing high concentrations of NO3- and enabled the environmentally friendly recovery of NH4+.

High-sensitivity dual U-shaped PCF-SPR refractive index sensor for the detection of gas and liquid analytes.

A dual U-shaped photonic crystal fiber (PCF) biochemical sensor based on surface plasmon resonance (SPR) is designed for the simultaneous detection of gas and liquid analytes, and the properties are analyzed by the full vector finite element method (FEM). SPR is excited by placing gold nanowires on the inner surface of the U-shaped device. In this technique, the traditional metal deposition process can be replaced, subsequently reducing the difficulty and complexity of actual production and improving the phase matching between the basic mode and plasmonic modes. To improve the detection properties, the structural parameters of the sensor including the air hole diameter, spacing, gold nanowire diameter, and polishing depth are optimized, and to better evaluate and analyze the sensing properties, the wavelength and amplitude modulation inquiry method is adopted. The results show that the maximum wavelength sensitivity (WS), amplitude sensitivity (AS), minimum resolution (R), and optimal FOM are 35,000 nm/RIU, 438.08R I U -1, 2.86×10-6 R I U, and 165.16R I U -1, respectively. In addition, the sensor can detect analyte RIs between 1.00 and 1.36 for gas and liquid analytes simultaneously. Owing to the simple structure, low cost, and ambient-condition monitoring, the sensor has large potential in a myriad of applications including sewage treatment, food safety, humoral regulation, environmental and biological monitoring, and medical diagnosis.

TripHLApan: predicting HLA molecules binding peptides based on triple coding matrix and transfer learning.

Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding motifs. Based on the discovery, we make the preprocessing and coding closer to the natural biological process. Besides, due to the input being based on multiple types of features and the attention module focused on the BiGRU hidden layer, TripHLApan has learned more sequence level binding information. The application of transfer learning strategies ensures the accuracy of prediction results under special lengths (peptides in length 8) and model scalability with the data explosion. Compared with the current optimal models, TripHLApan exhibits strong predictive performance in various prediction environments with different positive and negative sample ratios. In addition, we validate the superiority and scalability of TripHLApan's predictive performance using additional latest data sets, ablation experiments and binding reconstitution ability in the samples of a melanoma patient. The results show that TripHLApan is a powerful tool for predicting the binding of HLA-I and HLA-II molecular peptides for the synthesis of tumor vaccines. TripHLApan is publicly available at https://github.com/CSUBioGroup/TripHLApan.git.

Genomic survey and expression analysis of cellulose synthase superfamily and COBRA-like gene family in Zanthoxylum bungeanum stipule thorns.

The Cellulose Synthase gene (CS) superfamily and COBRA-like (COBL) gene family are essential for synthesizing cellulose and hemicellulose, which play a crucial role in cell wall biosynthesis and the hardening of plant tissues. Our study identified 126 ZbCS and 31 ZbCOBL genes from the Zanthoxylum bungeanum (Zb) genome. Phylogenetic analysis and conservative domain analysis unfolded that ZbCS and ZbCOBL genes were divided into seven and two subfamilies, respectively. Gene duplication data suggested that more than 75% of these genes had tandem and fragment duplications. Codon usage patterns analysis indicated that the ZbCS and ZbCOBL genes prefer ending with A/T base, with weak codon preference. Furthermore, seven key ZbCS and five key ZbCOBL genes were identified based on the content of cellulose and hemicellulose and the expression characteristics of ZbCS and ZbCOBL genes in various stages of stipule thorns. Altogether, these results improve the understanding of CS and COBL genes and provide valuable reference data for cultivating Zb with soft thorns. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-024-01432-x.

Risk assessment and molecular mechanism of Sclerotium rolfsii resistance to boscalid.

Boscalid, a widely used SDHI fungicide, has been employed in plant disease control for over two decades. However, there is currently no available information regarding its antifungal activity against Sclerotium rolfsii and the potential risk of resistance development in this pathogen. In this study, we evaluated the sensitivity of 100 S. rolfsii strains collected from five different regions in China during 2018-2019 to boscalid using mycelial growth inhibition method and assessed the risk of resistance development. The EC50 values for boscalid ranged from 0.2994 µg/mL to 1.0766 µg/mL against the tested strains, with an average EC50 value of 0.7052 ± 0.1473 µg/mL. Notably, a single peak sensitivity baseline was curved, indicating the absence of any detected resistant strains. Furtherly, 10 randomly selected strains of S. rolfsii were subjected to chemical taming to evaluate its resistance risk to boscalid, resulting in the successful generation of six stable and inheritable resistant mutants. These mutants exhibited significantly reduced mycelial growth, sclerotia production, and virulence compared to their respective parental strains. Cross-resistance tests revealed a correlation between boscalid and flutolanil, benzovindiflupyr, pydiflumetofen, fluindapyr, and thifluzamide; however, no cross-resistance was observed between boscalid and azoxystrobin. Thus, we conclude that the development risk of resistance in S. rolfsii to boscalid is low. Boscalid can be used as an alternative fungicide for controlling peanut sclerotium blight when combined with other fungicides that have different mechanisms of action. Finally, the target genes SDHB, SDHC, and SDHD in S. rolfsii were initially identified, cloned and sequenced to elucidate the mechanism of S. rolfsii resistance to boscalid. Two mutation genotypes were found in the mutants: SDHD-D111H and SDHD-H121Y. The mutants carrying SDHD-H121Y exhibited moderate resistance, while the mutants with SDHD-D111H showed low resistance. These findings contribute to our comprehensive understanding of molecular mechanisms underlying plant pathogens resistance to SDHI fungicides.

[Methods for traditional Chinese medicine syndrome-based efficacy evaluation: a review].

Traditional Chinese medicine(TCM) syndrome-based efficacy is an evaluation index which is unique to TCM and can reflect the advantages of TCM. The development of the methods and measurement tools for evaluating TCM syndrome-based efficacy can provide objective and quantitative evidence for the clinical efficacy evaluation of TCM and the development of new Chinese medicine preparations, being the exploration direction of innovative methods and technologies for evaluating TCM efficacy. The conventional evaluation methods are subjective and limited to the mitigation of symptoms and the improvement of physical signs, which make it difficult to form a unified evaluation standard. In addition, the evaluation methods lack unity, objectivity, and quantitative research. The scientific connotation, evaluation ideas and methods, and key technologies of the evaluation for the therapeutic effect on syndromes remain unclear, which leads to diverse evaluation modes, methods, and indexes. The syndrome-based efficacy scale provides a new idea for the objective quantification and standardization of TCM syndromes. This review systematically summarizes the methods and problems, introduces the research progress in the evaluation scales, and puts forward some thoughts on the characteristics of TCM syndrome-based efficacy evaluation, aiming to provide insights for the research in this field.

Water masses influence the variation of microbial communities in the Yangtze River Estuary and its adjacent waters.

The Yangtze River estuary (YRE) are strongly influenced by the Kuroshio and terrigenous input from rivers, leading to the formation of distinct water masses, however, there remains a limited understanding of the full extent of this influence. Here the variation of water masses and bacterial communities of 58 seawater samples from the YRE and its adjacent waters were investigated. Our findings suggested that there were 5 water masses in the studied area: Black stream (BS), coastal water in the East China Sea (CW), nearshore mixed water (NM), mixed water in the middle and deep layers of the East China Sea (MM), and deep water blocks in the middle of the East China Sea (DM). The CW mass harbors the highest alpha diversity across all layers, whereas the NM mass exhibits higher diversity in the surface layer but lower in the middle layers. Proteobacteria was the most abundant taxa in all water masses, apart from that, in the surface layer masses, Cyanobacterium, Bacteroidota, and Actinobacteriota were the highest proportion in CW, while Bacteroidota and Actinobacteriota were the highest proportion in NM and BS; in the middle layer, Bacteroidota and Actinobacteriota were dominant phylum in CW and BS masses, but Cyanobacterium was main phylum in NM mass; in the bottom layer, Bacteroidota and Actinobacteriota were the dominant phylum in CW, while Marininimicrobia was the dominated phylum in DM and MM masses. Network analysis suggests water masses have obvious influence on community topological characteristics, moreover, community assembly across masses also differ greatly. Taken together, these results emphasized the significant impact of water masses on the bacterial composition, topological characteristics and assembly process, which may provide a theoretical foundation for predicting alterations in microbial communities within estuarine ecosystems under the influence of water masses.

De novo diploid genome assembly using long noisy reads.

The high sequencing error rate has impeded the application of long noisy reads for diploid genome assembly. Most existing assemblers failed to generate high-quality phased assemblies using long noisy reads. Here, we present PECAT, a Phased Error Correction and Assembly Tool, for reconstructing diploid genomes from long noisy reads. We design a haplotype-aware error correction method that can retain heterozygote alleles while correcting sequencing errors. We combine a corrected read SNP caller and a raw read SNP caller to further improve the identification of inconsistent overlaps in the string graph. We use a grouping method to assign reads to different haplotype groups. PECAT efficiently assembles diploid genomes using Nanopore R9, PacBio CLR or Nanopore R10 reads only. PECAT generates more contiguous haplotype-specific contigs compared to other assemblers. Especially, PECAT achieves nearly haplotype-resolved assembly on B. taurus (Bison×Simmental) using Nanopore R9 reads and phase block NG50 with 59.4/58.0 Mb for HG002 using Nanopore R10 reads.

Study on heat transfer law of moving temperature variable gas in thermoacoustic plate stack.

Taking gas and the heat transfer process between gas and plate as the research object, the mathematical model of heat transfer in one working cycle by moving variable temperature air mass under the action of sound field is established, which provides a new idea for understanding thermoacoustic effect. The influence factors in the model are analyzed and it is found that the amplitude of the air mass has a significant influence on the heat transfer, and the heat transfer of the air mass in one working cycle is proportional to the square of the amplitude. In a certain working environment, the thermoacoustic refrigerator has a critical operating frequency, and only when the operating frequency is greater than the critical frequency can refrigeration be realized. The critical operating frequency is independent of the amplitude and increases with the increase of the stack temperature gradient. With the pressure belly point as the reference position, the greater the distance from the reference position, the greater the critical operating frequency. On this basis, the idea of short plate overlapping is put forward and the formation mechanism of temperature difference between two ends of plate overlapping is explained.

Recombinant bivalent subunit vaccine combining truncated VP4 from P[7] and P[23] induces protective immunity against prevalent porcine rotaviruses.

Porcine rotaviruses (PoRVs) cause severe economic losses in the swine industry. P[7] and P[23] are the predominant genotypes circulating on farms, but no vaccine is yet available. Here, we developed a bivalent subunit PoRV vaccine using truncated versions (VP4*) of the VP4 proteins from P[7] and P[23]. The vaccination of mice with the bivalent subunit vaccine elicited more robust neutralizing antibodies (NAbs) and cellular immune responses than its components, even at high doses. The bivalent subunit vaccine and inactivated bivalent vaccine prepared from strains PoRVs G9P[7] and G9P[23] were used to examine their protective efficacy in sows and suckling piglets after passive immunization. The immunized sows showed significantly elevated NAbs in the serum and colostrum, and the suckling piglets acquired high levels of sIgA antibodies from the colostrum. Challenging subunit-vaccinated or inactivated-vaccinated piglets with homologous virulent strains did not induce diarrhea, except in one or two piglets, which had mild diarrhea. Immunization with the bivalent subunit vaccine and inactivated vaccine also alleviated the microscopic lesions in the intestinal tissues caused by the challenge with the corresponding homologous virulent strain. However, all the piglets in the challenged group displayed mild to watery diarrhea and high levels of viral shedding, whereas the feces and intestines of the piglets in the bivalent subunit vaccine and inactivated vaccine groups had lower viral loads. In summary, our data show for the first time that a bivalent subunit vaccine combining VP4*P[7] and VP4*P[23] effectively protects piglets against the diarrhea caused by homologous virulent strains.IMPORTANCEPoRVs are the main causes of diarrhea in piglets worldwide. The multisegmented genome of PoRVs allows the reassortment of VP4 and VP7 genes from different RV species and strains. The P[7] and P[23] are the predominant genotypes circulating in pig farms, but no vaccine is available at present in China. Subunit vaccines, as nonreplicating vaccines, are an option to cope with variable genotypes. Here, we have developed a bivalent subunit candidate vaccine based on a truncated VP4 protein, which induced robust humoral and cellular immune responses and protected piglets against challenge with homologous PoRV. It also appears to be safe. These data show that the truncated VP4-protein-based subunit vaccine is a promising candidate for the prevention of PoRV diarrhea.

Mechanistic study of Huangqi Guizhi Wuwu decoction amelioration of doxorubicin-induced cardiotoxicity by reducing oxidative stress and inhibiting cellular pyroptosis.

Huangqi Guizhi Wuwu Decoction (HQGZWWD) has shown promising potential in treating various cardiovascular diseases. This study aimed to elucidate the molecular basis and therapeutic role of HQGZWWD in the treatment of doxorubicin (DOX)-induced myocardial injury. The HPLC fingerprint of HQGZWWD was used to analyze the active components. A DOX-induced myocardial damage rat model was developed, and the therapeutic effects of HQGZWWD were evaluated using echocardiography, myocardial enzyme levels, and hematoxylin and eosin staining. Network pharmacology was used to screen treatment targets, and western blotting and immunohistochemistry were performed to assess cellular pyroptosis levels. Oxidative stress levels were measured using assay kits, and mitochondrial damage was examined using transmission electron microscopy. An in vitro model of DOX-induced cell damage was established, and treatment was administered using serum containing HQGZWWD and N-acetylcysteine (NAC). Oxidative stress levels were detected using assay kits and DCFH-DA, whereas cellular pyroptosis levels were assessed through WB, immunofluorescence, and ELISA assays. HQGZWWD ameliorated DOX-induced myocardial injury. Network pharmacology identified IL-1ß and IL-18 as crucial targets. HQGZWWD downregulated the protein levels of the inflammatory factors IL-1ß and IL-18, inhibited the expression of GSDMD-NT, and simultaneously suppressed the synthesis of Caspase-1, ASC, NLRP3, and Caspase-11. Additionally, HQGZWWD inhibited oxidative stress, and the use of NAC as an oxidative stress inhibitor resulted in significant inhibition of the GSDMD-NT protein in H9C2 cells. These findings highlight the myocardial protective effects of HQGZWWD by inhibiting oxidative stress and suppressing both canonical and non-canonical pyroptotic pathways.

Methylated derivatives of polycyclic aromatic hydrocarbons in road dust, green belt soil and parking lot dust: occurrence, spatial distribution and emission sources.

Convenient transportation facilities not only bring the higher standard of living to big cities, but also bring some environmental pollution problems. In order to understand the presence and sources of methylated polycyclic aromatic hydrocarbons (Me-PAHs) in environmental samples and their association with total organic carbon (TOC), 49 Me-PAHs were analyzed in road dust, green belt soil and parking lot dust samples in Harbin. The results showed that the ranges of the total Me-PAHs (ΣMe-PAHs) content in road dust were 221-5826 ng/g in autumn and 697-7302 ng/g in spring, and those in green belt soil were 170-2509 ng/g and 155-9215 ng/g in autumn and spring, respectively. And ΣMe-PAHs content in parking lot dust ranged from 269 to 2515 ng/g in surface parking lots and from 778 to 10,052 ng/g in underground parking lots. In these samples, the composition profile of Me-PAHs was dominated by 4-ring Me-PAHs. The results of diagnostic ratios and principal component analysis (PCA) indicated that petrogenic and pyrogenic sources were the main sources of Me-PAHs in the samples. Spearman correlation analysis showed that there was no correlation for Me-PAHs in road dust and green belt soil on the same road. Furthermore, there was a significant positive relationship (0.12 ≤ R2 ≤ 0.67, P < 0.05) between Me-PAHs concentrations and the TOC content. This study demonstrated the presence of Me-PAHs with high concentrations in the road environment samples of Harbin.